Empirical method of diurnal correction for estimating sea surface temperature at dawn and noon

An empirical method has been developed for estimation of sea surface temperature (SST) at dawn and noon in local time from microwave observations at other times of the day. By using solar radiation, microwave sea surface wind, and SSTs, root-mean-square differences were reduced to approximately 0.75 and 0.8 °C for dawn and noon, respectively. The pseudo SST variation and spatial patterns found in daily mean SST values by simple averaging of samples were damped down by use of diurnal correction. The satellite SST with the diurnal correction shows highly significant coherent variation with in-situ measurements.     

Quality control methods for KOOS operational sea surface temperature products

Sea surface temperature SST obtained from the initial version of the Korea Operational Oceanographic System(KOOS) SST satellite have low accuracy during summer and daytime. This is attributed to the diurnal warming effect. Error estimation of SST data must be carried out to use the real-time forecasting numerical model of the KOOS. This study suggests two quality control methods for the KOOS SST system. To minimize the diurnal warming effect, SSTs of areas where wind speed is higher than 5 m/s were used. Depending on the wind threshold value, KOOS SST data for August 2014 were reduced by 0.15°C. Errors in SST data are considered to be a combination of random, sampling, and bias errors. To estimate bias error, the standard deviation of bias between KOOS SSTs and climatology SSTs were used. KOOS SST data yielded an analysis error standard deviation value similar to OSTIA and NOAA NCDC(OISST) data. The KOOS SST shows lower random and sampling errors with increasing number of observations using six satellite datasets. In further studies, the proposed quality control methods for the KOOS SST system will be applied through more long-term case studies and comparisons with other SST systems.     

Satellite-derived SST validation based on in-situ data during summer in the East China Sea and western North Pacific

Satellite-derived sea surface temperature (SST) is validated based on in-situ data from the East China Sea (ECS) and western North Pacific where most typhoons, which make landfall on the Korean peninsula, are formed and pass. While forecasting typhoons in terms of intensity and track, coupled ocean-typhoon models are significantly influenced by initial ocean condition. Potentially, satellite-derived SST is a very useful dataset to obtain initial ocean field because of its wide spatial coverage and high temporal resolution. In this study, satellite-derived SST from various sources such as Tropical Rainfall Measuring Mission Microwave Imager (TMI), Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E) and New Generation Sea Surface Temperature for Open Ocean (NGSST-O) datasets from merged SSTs were compared with in-situ observation data using an indirect method which is using near surface temperature for validation of satellite derived SST. In-situ observation data included shipboard measurements such as Expendable Bathythermograph (XBT), and Conductivity, Temperature, Depth (CTD), and Argo buoy data. This study shows that in-situ data can be used for microwave derived SST validation because homogeneous features of seawater prevail at water depths of 2 m to 10 m under favorable wind conditions during the summer season in the East China Sea. As a result of validation, root-mean-square errors (RMSEs) are shown to be 0.55 °C between microwave SST and XBT/CTD data mostly under weak wind conditions, and 0.7 °C between XBT/CTD measurement and NGSST-O data. Microwave SST RMSE of 0.55 °C is a potentially valuable data source for general application. Change of SST before and after typhoon passing may imply strength of ocean mixing due to upwelling and turbulent mixing driven by the typhoon. Based on SST change, ocean mixing, driven by Typhoon Nari, was examined. Satellite-derived SST reveals a significant SST drop around the track immediately following the passing of Typhoon Nari in October, 2007.     

Generation of high resolution sea surface temperature using multi-satellite data for operational oceanography

In the present article, we introduce a high resolution sea surface temperature(SST) product generated daily by Korea Institute of Ocean Science and Technology(KIOST). The SST product is comprised of four sets of data including eight-hour and daily average SST data of 1 km resolution, and is based on the four infrared(IR) satellite SST data acquired by advanced very high resolution radiometer(AVHRR), Moderate Resolution Imaging Spectroradiometer(MODIS), Multifunctional Transport Satellites-2(MTSAT-2) Imager and Meteorological Imager(MI), two microwave radiometer SSTs acquired by Advanced Microwave Scanning Radiometer 2(AMSR2), and Wind SAT with in-situ temperature data. These input satellite and in-situ SST data are merged by using the optimal interpolation(OI) algorithm. The root-mean-square-errors(RMSEs) of satellite and in-situ data are used as a weighting value in the OI algorithm. As a pilot product, four SST data sets were generated daily from January to December 2013. In the comparison between the SSTs measured by moored buoys and the daily mean KIOST SSTs, the estimated RMSE was 0.71°C and the bias value was –0.08°C. The largest RMSE and bias were 0.86 and –0.26°C respectively, observed at a buoy site in the boundary region of warm and cold waters with increased physical variability in the Sea of Japan/East Sea. Other site near the coasts shows a lower RMSE value of 0.60°C than those at the open waters. To investigate the spatial distributions of SST, the Group for High Resolution Sea Surface Temperature(GHRSST) product was used in the comparison of temperature gradients, and it was shown that the KIOST SST product represents well the water mass structures around the Korean Peninsula. The KIOST SST product generated from both satellite and buoy data is expected to make substantial contribution to the Korea Operational Oceanographic System(KOOS) as an input parameter for data assimilation.     

Difference characteristics of sea surface temperature observed by GLI and AMSR aboard ADEOS-II

This study compares infrared and microwave measurements of sea surface temperature (SST) obtained by a single satellite. The simultaneous observation from the Global Imager (GLI: infrared) and the Advanced Microwave Scanning Radiometer (AMSR: microwave) aboard the Advanced Earth Observing Satellite-II (ADEOS-II) provided an opportunity for the intercomparison. The GLI-and AMSR-derived SSTs from April to October 2003 are analyzed with other ancillary data including surface wind speed and water vapor retrieved by AMSR and SeaWinds on ADEOS-II. We found no measurable bias (defined as GLI minus AMSR), while the standard deviation of difference is less than 1°C. In low water vapor conditions, the GLI SST has a positive bias less than 0.2°C, and in high water vapor conditions, it has a negative (positive) bias during the daytime (nighttime). The low spatial resolution of AMSR is another factor underlying the geographical distribution of the differences. The cloud detection problem in the GLI algorithm also affects the difference. The large differences in high-latitude region during the nighttime might be due to the GLI cloud-detection algorithm. AMSR SST has a negative bias during the daytime with low wind speed (less than 7 ms⁻¹), which might be related to the correction for surface wind effects in the AMSR SST algorithm.     

Assessment of the initial sea surface temperature product of the scanning microwave radiometer aboard on HY-2 satellite

HY-2 satellite is the first satellite for dynamic environmental parameters measurement of China,which was launched on 16th August 2011.A scanning microwave radiometer（RM） is carried for sea surface temperature（SST）,sea surface wind speed,columnar water vapor and columnar cloud liquid water detection.In this paper,the initial SST product of RM was validated with in-situ data of National Data of Buoy Center（NDBC） mooring and Argo buoy.The validation results indicate the accuracy of RM SST is better than 1.7 C.The comparison of RM SST and WindSat SST shows the former is warmer than the latter at high sea surface wind speed and the difference between these SSTs is depend on the sea surface wind speed.Then,the relationship between the errors of RM SST and sea surface wind speed was analyzed using NDBC mooring measurements.Based on the results of assessment and errors analysis,the suggestions of taking account of the affection of sea surface wind speed and using sea surface wind speed and direction derived from the microwave scatteromter aboard on HY-2 for SST product calibration were given for retrieval algorithm improvement.     

Numerical Simulation of North Indian Ocean State Prior to the Onset of SW Monsoon Using SSM/I Winds

The Sea Surface Temperatures (SST) and currents are simulated over the north Indian Ocean, during the onset phase of southwest monsoon for the three years 1994, 1995, and 1996, using daily Special Sensor Microwave/Imager (SSM/I) winds and National Center for Environmental Prediction (NCEP) heat fluxes as forcings in the 2½ layer thermodynamic numerical ocean model. The results are discussed for the 30-day period from 16 May to 13 June for all the three years, to determine the ocean state during the onset phase of SW monsoon. The maximum variability in the simulated SST is found along the Somali coast, Indian coasts, and equatorial regions. The maximum SST in the North Arabian Sea is found to be greater than 30°C and minimum SST in the west equatorial region is 25°C during the onset phase of all three years. Model SSTs are in agreement with Reynolds SST. SST gradients in the north-south as well as in the east-west directions, west of 80°E are found to change significantly prior to the onset. It can be inferred from the study that the SST gradient of 2.5°C/2000 km is seen due north and due west of the region 2° - 7°S, 60° - 65°E, about 8 to 10 days prior to the arrival of SW monsoon near Kerala coast. Upper and lower layer circulation fields do not show prominent interannual variability.     

Merging satellite infrared and microwave SSTs: Methodology and evaluation of the new SST

The Global Ocean Data Assimilation Experiment (GODAE) requires the availability of a global analyzed SST field with high-resolution in space (at least 10 km) and time (at least 24 hours). The new generation SST products would be based on the merging of SSTs from various satellites data and in situ measurements. The merging of satellite infrared and microwave SST data is investigated in this paper. After pre-processing of the individual satellite data, objective analysis was applied to merge the SST data from NOAA AVHRR (National Oceanic and Atmospheric Administration, Advanced Very High Resolution Radiometer), GMS S-VISSR (Geostationary Meteorological Satellite, Stretched-Visible Infrared Spin Scan Radiometer), TRMM MI (Tropical Rainfall Measuring Mission, Microwave Imager: TMI) and VIRS (Visible and Infrared Scanner). The 0.05° daily cloud-free SST products were generated in three regions, viz., the Kuroshio region, the Asia-Pacific Region and the Pacific, during one-year period of October 1999 to September 2000. Comparisons of the merged SSTs with Japan Meteorological Agency (JMA) buoy SSTs show that, with considerable error sources from individual satellite data and merging procedure, an accuracy of 0.95 K is achieved. The results demonstrate the practicality and advantages of merging SST measurements from various satellite sensors.     

Surface heat fluxes during hot events

We selected surface flux datasets to investigate the heat fluxes during “hot events”; (HEs), defined as short-term, large-scale phenomena involving very high sea surface temperature (SST). Validation of the heat fluxes against in-situ ones, which are estimated from in-situ observation in HE sampling conditions, shows the accuracies (bias ± RMS error) of net shortwave radiation, net long wave radiation, latent heat and sensible heat fluxes are 20 ± 45.0 W m⁻², −9 ± 12.3 W m⁻², −2.3 ± 31.5 W m⁻² and 1.5 ± 5.0 W m⁻², respectively. Statistical analyses of HEs show that, during these events, net solar radiation remains high and then decreases from 246 to 220 W m⁻², while latent heat is low and then increases from 100 W m⁻² to 124 W m⁻². Histogram peaks indicate net solar radiation of 270 W m⁻² and latent heat flux of 90 W m⁻² during HEs. Further, HEs are shown to evolve in three phases: formation, mature, and ending phases. Mean heat gain (HG) in the HE formation phase of 60 W m⁻² is larger than the reasonably estimated annual mean HG range of 0–25 W m⁻² in the Indo-Pacific Warm Pool. Such large daily HG in the HE formation phase can be expected to increase SSTs and produce large amplitudes of diurnal SST variations during HEs, which have been observed by both satellite and in-situ measurements in our previous studies.     

Study on SST front disappearance in the subtropical North Pacific using microwave SSTs

We investigated the processes relating to the weakening of the SST front in the subtropical front (STF) zone using the Advanced Microwave Scanning Radiometer for the Earth Observing System SSTs for 7?years with temporal/spatial resolutions of 1?day/12.5?km. In April, the SST front is strong with a high gradient magnitude (GM) and Jensen–Shannon divergence (JSD) band; in August, SSTs become uniform (28–30?°C), together with small GMs (<0.8?°C/100?km) and JSDs (<0.75). Since the SST front features become invisible in GM/JSD snapshots and weekly–monthly averaged images, we call this phenomenon ‘SST front disappearance (SFD)’. The SFD occurs in August, but the number of high SSTs (>30?°C) in August is smaller than that in July, which indicates that the SFD results from not only the increase in lower SSTs but also the decrease in higher SSTs. In June and July, the GM distributions have quite large standard deviations compared to those in May and August. We also investigated the vertical profile of STF using in situ temperature/salinity profiles. It was revealed that the SFD influence extends to 50?m depth. The area of high integrated heat flux and shallow mixed layer depth were found to correspond to the area where the GM decreases from 0.9 to 0.6?°C/100?km during June–August. Quantitative analyses confirmed that the SFD mechanism may be attributable to the establishment of the shallow mixed layer by the high integrated heat flux from May to July. From July to August, the SST heating/cooling in the north/south of the SST front may accelerate the SFD.     

North Brazil current rings viewed by TRMM Microwave Imager SST and the influence of the Amazon Plume

In the western equatorial Atlantic, 5 years of satellite Sea Surface Temperature (SST) measurements (1998–2002) from the cloud penetrating Tropical Rainfall Measuring Mission (TRMM) Microwave Imager reveal SST signatures of rings shedding from the North Brazil Current (NBC) as it separates from the South American coastline north of the Amazon River Delta and retroflects eastward between 5 and 10°N. By removing the spatial-mean SST from a 7° by 7° square of the nearly instantaneous measurements of each satellite pass, the 46.7 day aliasing period of the diurnal solar cycle is reduced, and seven to eight rings are observed per year with relatively warm (cold) SST anomalies of up to 1 °C in the first (second) half of the year. The sense of the SST anomalies carried by the NBC rings are determined by the contrast between the NBC SST and the regional SSTs that are influenced by the far-reaching seasonally varying Amazon River freshwater plume. Within a 1.6-year period, 12 of the SST anomalies are validated by in situ mooring array data confirming the predicted sense of the SST anomalies for each season. According to historical hydrographic data, during the first half of the year, the Amazon Plume is generally contained northwest along the coast, whereas during the second half of the year, the Amazon Plume surrounds the NBC retroflection on the west and the north, and from the surface down to 50 m, imposing a dramatic surface salinity contrast up to −4 and a surface temperature contrast up to +2 °C across the front. The surface layer characteristics of the rings shed from the NBC retroflection reveal varying influence of the Amazon Plume. Of the four rings surveyed in the NBCR experiment, Amazon Plume water is found only on the edges of three surface-intensified rings, whereas it completely covers the surface layer of the one thermocline-intensified ring. The maximum current cores of the NBC and retroflection are observed within tens-of-meters of the edges of the Amazon Plume. As the fresher and typically warmer surface waters associated with the Amazon Plume are buoyant relative to the saltier and typically colder surface waters carried by the NBC, the varying position of the Amazon Plume may seasonally influence the surface dynamics in the region.     

Validation of Daily Amplitude of Sea Surface Temperature Evaluated with a Parametric Model Using Satellite Data

The authors have verified a regression model for the evaluation of the daily amplitude of sea surface temperature (ΔSST) proposed by Kawai and Kawamura (2002). The authors investigated the accuracy of satellite data used for the evaluation and showed that ΔSST error caused by satellite data error is less than ±0.7 K. The evaluated ΔSSTs were compared with in situ values. Its root-mean-square error is about 0.3 K or less, except for a coastal region, and it has a bias of more than +0.1 K in the tropics. This bias can be removed by considering latent heat flux. This revised version was published online in July 2006 with corrections to the Cover Date.     

Hourly sea surface temperature retrieval using the Japanese Geostationary Satellite,Multi-Functional Transport Satellite (MTSAT)

An algorithm has been developed for retrieving sea surface temperature (SST) from hourly data transmitted from the Japanese Advanced Meteorological Imager (JAMI) aboard a Japanese geostationary satellite, Multi-functional Transport Satellite (MTSAT)-1R. Threshold tests screening cloudy pixels are empirically adjusted to cases of daytime with/without sun glitter, and nighttime. The Non-Linear SST (NLSST) equation, including several new additional terms, is used to calculate MTSAT SST. The estimated SST is compared with drifting and moored buoy measurements, with the result that the bias of the MTSAT SST is nearly 0.0°K. The root mean square (rms) error is about 0.8°K, and it is 0.7°K under the condition that the satellite zenith angle is less than 50°. It is demonstrated that the hourly MTSAT SST produced by the algorithm developed here captures diurnal SST variations in the equatorial sea in mid-November 2006.     

An offshore eddy in the California current system part II: Surface manifestation

Ship and satellite observations taken over the last thirty years show that mesoscale patterns of sea surface temperature (SST) in the California Current System are consistently found throughout the year and usually occur in approximately the same geographical locations. Typically, these patterns are more pronounced in fall/winter than in spring/summer. The temporal and spatial characteristics of these persistent feature were examined with satellite infrared (IR) measurements during winter 1980–1981. In January 1981, a ship surveyed the vertical structure of several physical, chemical, and biological parameters beneath one of these SST features centered near 32°N, 124°W. The surface IR pattern had a length scale of 200 km and a time scale of about 100 days. It disintegrated following the first two storms of the winter season. Motion studies of the pattern in late October indicated an anticyclonic rotation with maximum velocities of 50 cm s^?1 at 50 km from the axis of rotation. As a unit, the pattern advected southward with an average speed of 1 cm s^?1. Thermal fronts, determined from the satellite imagery, were strongest (0.4°C km^?1) along the rim of the pattern and were advected anticyclonically with the pattern; their length scales were 20–30 km in the along-front direction and less than 10 km wide. The hydrographic data revealed a three-layer structure beneath the surface pattern; a 75 m deep surface layer, a cold-core region from 75 to 200 m depth, and a warm-core eddy extending from 250 to 1450 m. The anticyclonic motion of the surface layer was caused by a geostrophic adjustment to the surface dynamic height anomaly produced by the subsurface warm-core eddy. The IR pattern observed from space reflects the horizontal structure of the surface layer and is consistent with a theoretical model of a mean horizontal SST gradient perturbed by a subsurface density anomaly. Ship of opportunity SST observations collected by the National Marine Fisheries are shown to resolve mesoscale patterns. For December 1980, the SST pattern near 32°N, 124°W represented a 2°C warm anomaly compared with the 20-year mean monthly SST pattern.     

基于最优插值方法的微波-红外辐射计数据融合全球海面温度网格产品

A new 0.1° gridded daily sea surface temperature(SST) data product is presented covering the years 2003–2015. It is created by fusing satellite SST data retrievals from four microwave(Wind Sat, AMSR-E, ASMR2 and HY-2 A RM)and two infrared(MODIS and AVHRR) radiometers(RMs) based on the optimum interpolation(OI) method. The effect of including HY-2 A RM SST data in the fusion product is studied, and the accuracy of the new SST product is determined by various comparisons with moored and drifting buoy measurements. An evaluation using global tropical moored buoy measurements shows that the root mean square error(RMSE) of the new gridded SST product is generally less than 0.5℃. A comparison with US National Data Buoy Center meteorological and oceanographic moored buoy observations shows that the RMSE of the new product is generally less than 0.8℃. A comparison with measurements from drifting buoys shows an RMSE of 0.52–0.69℃. Furthermore, the consistency of the new gridded SST dataset and the Remote Sensing Systems microwave-infrared SST dataset is evaluated, and the result shows that no significant inconsistency exists between these two products.     

Research and development of the New Generation Sea Surface Temperature for Open Ccean (NGSST-O) product and its demonstration operation

Real-time generation and distribution of the New Generation Sea Surface Temperature for Open Ocean (NGSST-O) product began in September 2003 as a demonstration operation of the Global Ocean Data Assimilation Experiment (GODAE) High-Resolution Sea Surface Temperature Pilot Project. Satellite sea surface temperature (SST) observations from infrared radiometers (AVHRR, MODIS) and a microwave radiometer (AMSR-E) are objectively merged to generate the NGSST-O product, which is a quality-controlled, cloud-free, high-spatial-resolution (0.05° gridded), wide-coverage (13–63° N, 116–166° E), daily SST digital map. The NGSST-O demonstration operation system has been developed in cooperation with the Japanese Space Agency (JAXA) and has produced six years of continuous data without gaps. Comparison to in situ SSTs measured by drifting buoys indicates that the root mean-square error of NGSST-O has been kept at approximately 0.9°C.     

TMI、AMSR-E全球海表温度与Argo近海表温度的比较

本文将TMI（Tropical Rainfall Measuring Mission （TRMM）Microwave Imager）和AMSR-E（Advanced Microwave Scanning Radiometer for the Earth Observing System）卫星观测的全球海表温度与Argo浮标观测的近海表温度进行了比较。并检验了影响海温变化的因素,包括风速、水汽含量、液态云和地理位置。结果显示,TMI、AMSR-E海表温度与Argo近海表温度均明显相关。在低风速时,TMI、AMSR-E海表温度整体比Argo近海表温度高。在低风速时,TMI比AMSR-E海表温度更接近Argo近海表温度,但TMI海表温度在高纬可能没有经过良好校正。温度差异显示,在低水汽含量时,TMI和AMSR-E海表温度显示出暖的差异,代表TMI和AMSR-E海表温度在高纬均没有经过良好校正。黑潮延伸区的海表温度变化要比海潮区明显。春季在黑潮延伸区,卫星观测的海表温度与Argo近海表温度差异较小。在低风速时,TMI和AMSR-E海表温度均经过了良好校正,而TMI比AMSR-E效果更好。     

利用卫星资料分析黄海海表温度的年际与年代际变化

海表温度长期变化在一定程度上反映了海域的气候变化信号,卫星遥感资料是获取高时空分辨率水温长期变化的有效手段。基于国家海洋局1982—1999年黄海断面监测器测数据的2 954组水温数据对时空匹配的卫星(NOAA/AVHRR)反演海表温度(SST)进行校验,计算得到卫星反演SST系统偏差为(0.18±1.00)℃。卫星反演的水温空间分布以及长期变化趋势与器测趋势较为一致,可以用来研究海域SST长期变化规律。利用校验后1982-01～2011-08NOAA/AVHRR的SST数据,分析了该时段黄海冬夏季代表月2、8月海表水温的变化规律。结果显示:(1)近30a,黄海冬季水温有2次跃迁:1989—1990年由冷至暖的状态跃迁,2000-2001年出现由暖至冷的状态转变;1990年代冬季水温达最高,相比1880年代,水温升高1.07℃,新世纪水温稍有降低,水温较1990年代下降了0.53℃,温度变化较大区域位于北黄海、山东半岛沿岸,苏北浅滩毗邻海区,该区SST与局地经向风场存在显著正相关,且北极涛动通过影响冬季风间接影响黄海水温变化;(2)夏季海表水温在1994—1995年呈现由冷至暖的状态跃迁,冷、暖期水温相差0.57℃,水温变化较显著的区域为黄东海分界处,其具体变化机制需深入研究。     

Estimation of sea surface temperatures around Japan using the advanced very high resolution radiometer (AVHRR)/NOAA-11

The accuracy of sea surface temperatures (SSTs) derived from the Advanced Very High Resolution Radiometer (AVHRR)/NOAA-11 is examined by comparison with sea-truth SSTs obtained from ocean data buoys durings November 1988 through December 1989. We made a 122 point data set of buoy SSTs from the oceans around Japan and the corresponding brightness temperatures of channels 4 and 5 during cloud free periods. The satellite temperatures are corrected for atmospheric effects using the NOAA Multi-Channel SST (MCSST) and Cross Product SST (CPSST) algorithms. The two algorithms give similar results for our data set and result in biases of about –0.1°C with rms errors of about 0.6°C relative to buoy SSTs. It is found that MCSSTs and CPSSTs tend to be higher than SSTs from the buoy in the Japan Sea in summer. New coefficients for the MCSST equations suitable for our data set are determined and the resultant rms error is 0.49°C. If we eliminate the cluster of anomalous summer data in the Japan Sea, the rms error becomes 0.43°C.     

Advanced sea surface temperature retrieval using the Japanese geostationary satellite,Himawari-6

Producing high-quality match-ups coupling the Japanese geostationary satellite, Himawari-6 (H6), and buoy SST observations, we have developed the new SST retrieval method. Kawamura et al. (2010) developed the previous version of SST product called MTSAT SST, which left several scientific/technical questions. For solving them, 6,711 algorithm tuning match-ups with precise navigation and 240,476 validation match-ups are generated for covering all seasons and wide ocean coverage. For discriminating the previous MTSAT SST, we call the new version of SST H6 SST. It is found that the SZA dependences of MTSAT SST algorithm are different from area to area of SZA > 40–50° N/S. The regionally different SZA dependences are treated by dividing the H6 disk coverage into five areas by the latitude lines of 40° N/S first and the longitude lines of 100° K and 180° K. Using the algorithm tuning match-ups, Nonlinear SST (NLSST) equations are derived for all of the five areas. Though the sun zenith angle dependency correction term is also examined, there is no significant regional difference. Therefore, this term is used in the H6 SST algorithm again. The new H6 SST equation is formed by the areal NLSST and the sun zenith angle dependency term for each area. The statistical evaluation of H6 SST using the validation match-ups show the small negative biases and the RMS errors of about 0.74° K for each area. For the full H6 disk, the bias is −0.1° K and the RMS error 0.74° K. The histogram of H6 SST minus the in situ SST for each area has a similar Gaussian shape with small negative skewness, and the monthly validation of H6 SST for each area is consistent with those for the whole period and the histograms